291–300 of 328 posts
If Google won, it would cannibalize its current ad-driven business and replace it with something that is extremely expensive to run and difficult to make profit from. A Pyrrhic win essentially.
- Google is not owning the technology but builds a cohesive cloud around it, Tesla, Meta work on their own asic ai chips and I guess others
- A signal is already given: Softbank sold it's entire Nvidia stock and berkshire added google on their portfolio.
Microsoft "has" a lot of companies data, and google is probably building the most advanced ai cloud.
However, I can't think they had a cloud which was light-years ahead of aws 15 years ago and now GCP is no 3, they also released opensource gpt models more than 5 years ago that constituted the foundation for openai closed sourced models.
Earlier quoted context omitted.
Deepmind gets to work directly with the TPU team to make custom modifications and designs specifically for deepmind projects. They get to make pickaxes that are made exactly for the mine they are working. Everyone using Nvidia hardware has a lot of overlap in requirements, but they also all have enough architectural differences that they won't be able to match Google. OpenAI announced they will be designing their own…
> Deepmind gets to work directly with the TPU team to make custom modifications You don't think Nvidia has field-service engineers and applications engineers with their big customers? Come on man. There is quite a bit of dialogue between the big players and the chipmaker.
Deepmind can do whatever they want, and get the exact hardware to match it. It's a massive advantage when you can discover a bespoke way of running a filter, and you can get a hardware implementation of it without having to share that with any third parties. If OpenAI takes a new find to Nvidia, everyone else using Nvidia chips gets it too.
Earlier quoted context omitted.
Modern CUDA programs that hit roofline look absolutely nothing like those from 10 or even 5 years ago. Or even 2 if you’re on Blackwell.
But for research you often don't have to max out the hardware right away. And the question is what do programs that max out Ironwood look like vs TPU programs written 5 years ago?
I always enjoy being wrong and I was very wrong in my predictions about Google : I thought they should theoretically win, but I was also very confident they couldn't possibly turn their execution ship around to actually pull together a coherent competitor to OpenAI. But they do seem to have done that and it's very impressive. If they do continue to execute, I can't see anybody stopping them dominating and I would be…
The LLM provider I trust the most right now is AWS. Anybody else seems to have very conflicted purposes when it comes to sending them my data and interactions.
I don't think what the article writes about matters all that much. Gemini 3 Pro is arguably not even the best model anymore, and it's _weeks_ old, and Google has far more resources than Anthropic does. If the hardware actually was the secret sauce, Google would be wiping the floor with little everyone else. But they're not. There's a few confounding problems: 1. Actually using that hardware effectively isn't easy. It…
I think you are addressing the issue from a developer's perspective. I don't think TPUs are going to be sold to individual users anytime soon. What the article is pointing out is that Google is now able to squeeze significantly more performance per dollar than their peer competitors in the LLM space. For example, OpenAI has announced trillion-dollar investments in data centers to continue scaling. They need to go thr…
Performance per dollar doesn't "win" anything though. Performance (as in speed) hardly cracks the top five concerns that most folks have when choosing a model provider, because fast, good models already exist at price points that are acceptable. That might mean slightly better margins for Google, but ultimately isn't going to make them "win"
I don't think what the article writes about matters all that much. Gemini 3 Pro is arguably not even the best model anymore, and it's _weeks_ old, and Google has far more resources than Anthropic does. If the hardware actually was the secret sauce, Google would be wiping the floor with little everyone else. But they're not. There's a few confounding problems: 1. Actually using that hardware effectively isn't easy. It…
They are using that hardware to wipe the floor with everyone if you look at the price per million tokens.
I don't think what the article writes about matters all that much. Gemini 3 Pro is arguably not even the best model anymore, and it's _weeks_ old, and Google has far more resources than Anthropic does. If the hardware actually was the secret sauce, Google would be wiping the floor with little everyone else. But they're not. There's a few confounding problems: 1. Actually using that hardware effectively isn't easy. It…
"Gemini 3 Pro is arguably not even the best model anymore" Arguably indeed, because I think it still is.
Which is to say, if Google was set up to win, it shouldn't even be a question that 3 Pro is the best. It should be obvious. But it's definitely not obvious that it's the best, and many benchmarks don't support it as being the best.
I don't think what the article writes about matters all that much. Gemini 3 Pro is arguably not even the best model anymore, and it's _weeks_ old, and Google has far more resources than Anthropic does. If the hardware actually was the secret sauce, Google would be wiping the floor with little everyone else. But they're not. There's a few confounding problems: 1. Actually using that hardware effectively isn't easy. It…
Fairly certain google is aiming for "realtime" model training which would definitely require a new arcjitscture